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Data Engineer (PySpark, Hadoop and AWS)

 A leading bank with commercial, international, and private banking services is undergoing a major digital transformation and shift towards using public cloud. We are entrusted with building the leadership and tech team to bring in experienced professionals who can help in the transformation.


  • Work with new technology, focus on using the right tool for the job, rather than any sticky preference for a tool or technology
  • Learn and share knowledge across our engineering teams, so we can continue to iterate and improve
  • Write reusable, testable, and efficient code
  • Creates and manages schema and instances for SQL and non-SQL databases
  • Design and implement low-latency, high-availability, and performant applications
  • Write data pipelines that access multiple systems to retrieve, validate, process, and store data
  • Integrate user-facing elements developed by front-end developers with server-side logic
  • Work on implementation of security and data protection projects
  • Collaborate and work on the integration of data storage solutions
  • Focus on performance tuning, improvement, balancing, usability, and automation

What does a typical day look like:

  • Data Analysis (20%)
  • Development (40%)
  • Testing (20%)
  • Deployment activities (20%)